Sobre este puesto de Machine Learning Engineer en Ramp
About Ramp
Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $275B in annualized spend flows in and out of 85,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books.
The problems are high-stakes, data-dense, and unforgiving.
We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome.
The median Ramp customer saves 7.5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same.
If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it.
About the Role
We’re seeking someone to lead the future of fraud machine learning at Ramp. In this role, you will help build core machine learning models, design data architectures, and set strategic roadmaps to help Ramp mitigate fraud-related threats while minimizing the friction experience by legitimate users. You will partner closely with product and engineering counterparts across model design, implementation, execution, and analysis.
What You’ll Do
Employ statistical and machine learning techniques on large datasets to discover patterns of fraud, platform abuse, and identity theft
Prototype and productionize machine learning models and rules-based systems to protect Ramp and its users from fraud
Partner closely with Fraud Engineering and Data Platform teams to augment and leverage data across first and third party sources, ensuring we’ve added as much context as possible to every decision we make
Contribute to the culture of Ramp’s machine learning team by influencing processes, tools, and systems that will allow us to make better decisions in a scalable way
What You Need
Bachelor’s degree or above in Math, Economics, Physics, Computer Science, or other quantitative fields
A minimum of 5 years of industry experience as a Machine Learning Engineer, Applied Scientist or Data Scientist
Strong python experience (numpy, pandas, sklearn, pytorch etc.) across ML techniques and backend engineering
Prior experience deploying Machine Learning models to production and making meaningful contribution to backend systems
Strong knowledge of SQL (Snowflake, Postgres, etc.)
Fluency with agentic (AI) tools for software development and data analysis
Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutions
Nice-to-Haves
PhD in Math, Economics, Physics, Computer Science, or other quantitative fields
Context on Fraud and/or Identity Threat detection systems
Experience at a high-growth startup
Experience with the modern data stack ( Snowflake / Hex / dbt / RisingWave / etc )
Strong perspective on data science + ML engineering development cycle, especially in a post-AI setting
Experience developing LLM-backed systems or tools
Benefits available to all full-time Ramp employees (Global)
Flexible PTO
Centralized home-office equipment ordering
Health and wellness stipend
Budget for intra-office travel
Weekly coffee stipend
United States
100% medical, dental & vision insurance coverage for you, with partial coverage for dependents
One Medical annual membership
401(k), including employer match on contributions made while employed by Ramp
Fertility HRA (up to $10,000 per year)
Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay
Pet insurance
In-office perks: lunch, snacks, drinks, and more
Relocation expense coverage to NYC or SF (if needed)
Canada
Group medical, dental, and vision coverage through Sun Life
Life, AD&D, and disability coverage
Fertility drug coverage (up to $4,000 lifetime)
Group Retirement Plan with employer match (RRSP + DPSP)
Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay
Employee Assistance Program and virtual care through Lumino Health
United Kingdom
Private medical insurance through Freedom Elite
Virtual GP and at-home care via eMed x Livi
Workplace pension through Penfold, with salary sacrifice option
Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay
Referral Instructions
If you are being referred for the role, please contact that person to apply on your behalf.
Other notices
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Beware of recruiting scams: Ramp will only contact you through official @Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.
